Avoidance of moving obstacles through behavior fusion and motion prediction

In this paper, we propose a novel approach of fusing the fuzzy control actions of the obstacle avoidance, goal seeking and steering behaviors, in which the steering behavior is derived from motion prediction. As such, the navigator is more capable to steer clear of the zone of high collision probability. Through simulation, it has been confirmed that the navigator having this steering behavior can tackle multiple moving obstacles successfully at much higher speed compared with those without. Furthermore, it does not require any a priori knowledge of the obstacles' motion.published_or_final_versio

Collision avoidance by a modified least-mean-square-error classification scheme for indoor autonomous land vehicle navigation

[[abstract]]In this article, a new collision-avoidance scheme is proposed for autonomous land vehicle (ALV) navigation in indoor corridors. The goal is to conduct indoor collisionfree navigation of a three-wheel ALV among static obstacles with no a priori position information as well as moving obstacles with unknown trajectories. Based on the predicted positions of obstacles, a local collision-free path is computed by the use of a modified version of the least-mean-square-error (LMSE) classifier in pattern recognition. Wall and obstacle boundaries are sampled as a set of 2D coordinates, which are then viewed as feature points. Different weights are assigned to different feature points according to the distances of the feature points to the ALV location to reflect the locality of path planning. The trajectory of each obstacle is predicted by a real-time LMSE estimation method. And the maneuvering board technique used for nautical navigation is employed to determine the speed of the ALV for each navigation cycle. Smooth collision-free paths found in the simulation results are presented to show the feasibility of the proposed approach

Collision Avoidance by a modified least-mean- square-error classification scheme for indoor autonomous land vehicle navigation

[[abstract]]In this article, a new collision-avoidance scheme is proposed for autonomous land vehicle (ALV) navigation in indoor corridors. The goal is to conduct indoor collisionfree navigation of a three-wheel ALV among static obstacles with no a priori position information as well as moving obstacles with unknown trajectories. Based on the predicted positions of obstacles, a local collision-free path is computed by the use of a modified version of the least-mean-square-error (LMSE) classifier in pattern recognition. Wall and obstacle boundaries are sampled as a set of 2D coordinates, which are then viewed as feature points. Different weights are assigned to different feature points according to the distances of the feature points to the ALV location to reflect the locality of path planning. The trajectory of each obstacle is predicted by a real-time LMSE estimation method. And the maneuvering board technique used for nautical navigation is employed to determine the speed of the ALV for each navigation cycle. Smooth collision-free paths found in the simulation results are presented to show the feasibility of the proposed approach

Autonomous mobile robot navigation using fuzzy logic control

Traditionally the type of robot used in the workplace consisted mainly o f the fixed arm variety. Any mobile robots that were commercially available required that the environment be altered to accommodate them. This involved the installation of guide lanes or some form of sensor units placed at various locations around the workplace to facilitate the robot in determining its position within the environment. Such approaches are costly and limit the use of robots to environments where these methods are feasible. The inadequacies in this technology has led to research into autonomous mobile robots that offer greater flexibility and do not require changes in the enviromnent. There are many technical issues to be addressed in designing such a robot. These stem from the necessity that the robot must be able to navigate through an environment unaided. Other problems such as the cost of the vehicle must be considered so that prospective customers will not be put off. This thesis discusses the strategies taken in addressing the problems associated with navigation in an obstacle strewn environment. Such issues include position estimation, path planning, obstacle avoidance and the acquisition and interpretation of sensor information. It also discusses the suitability of fuzzy logic for controlling a robot. A graphical user interface runs on the PC which communicates with the robot over a radio link. The robot uses a fuzzy logic controller to follow a planned path and avoid unknown obstacles by controlling the velocity and steering angle o f the drive unit. It is a tracked vehicle which is suitable for indoor use only. The results of path planning and the robots attempts at following the paths and avoiding obstacles are illustrated and discussed